Reconstruction and error detection of blood vessel network from ultrasound volume data

Kohji Masuda; Antoine Bossard; Yuki Sugano; Toshikazu Kato; Shinya Onogi

doi:10.1109/CBMS.2013.6627850

Reconstruction and error detection of blood vessel network from ultrasound volume data

Kohji Masuda, Antoine Bossard, Yuki Sugano, Toshikazu Kato, Shinya Onogi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Recently, we described a reconstruction method of the blood vessel network by 3D thinning to detect vessels bifurcations, which is applied to the control of microbubbles in vivo. However, that method did not include error detections and was only verified on a very simply shaped artificial blood vessel. In this paper we propose a system including an abstraction method for the blood vessel network. Such a model is then analyzed through graph theory and error patterns in the reconstructed network. We proceeded in vitro by acquiring volume data from an artificial capillary with multi-bifurcations whose diameter ranges from 0.5 to 2.0mm and with different flow velocities. We were able to reconstruct the blood vessel network of an in vitro artificial capillary with multi-bifurcations. Results show that our system successfully reconstructed the corresponding networks as much as the limitation of resolution of echography.

Original language	English
Title of host publication	Proceedings of CBMS 2013 - 26th IEEE International Symposium on Computer-Based Medical Systems
Pages	497-501
Number of pages	5
DOIs	https://doi.org/10.1109/CBMS.2013.6627850
Publication status	Published - 2013
Externally published	Yes
Event	26th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2013 - Porto, Portugal Duration: Jun 20 2013 → Jun 22 2013

Other

Other	26th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2013
Country/Territory	Portugal
City	Porto
Period	6/20/13 → 6/22/13

All Science Journal Classification (ASJC) codes

Biomedical Engineering
Health Informatics

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10.1109/CBMS.2013.6627850

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Masuda, K, Bossard, A, Sugano, Y, Kato, T & Onogi, S 2013, Reconstruction and error detection of blood vessel network from ultrasound volume data. in Proceedings of CBMS 2013 - 26th IEEE International Symposium on Computer-Based Medical Systems., 6627850, pp. 497-501, 26th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2013, Porto, Portugal, 6/20/13. https://doi.org/10.1109/CBMS.2013.6627850

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title = "Reconstruction and error detection of blood vessel network from ultrasound volume data",

abstract = "Recently, we described a reconstruction method of the blood vessel network by 3D thinning to detect vessels bifurcations, which is applied to the control of microbubbles in vivo. However, that method did not include error detections and was only verified on a very simply shaped artificial blood vessel. In this paper we propose a system including an abstraction method for the blood vessel network. Such a model is then analyzed through graph theory and error patterns in the reconstructed network. We proceeded in vitro by acquiring volume data from an artificial capillary with multi-bifurcations whose diameter ranges from 0.5 to 2.0mm and with different flow velocities. We were able to reconstruct the blood vessel network of an in vitro artificial capillary with multi-bifurcations. Results show that our system successfully reconstructed the corresponding networks as much as the limitation of resolution of echography.",

author = "Kohji Masuda and Antoine Bossard and Yuki Sugano and Toshikazu Kato and Shinya Onogi",

year = "2013",

doi = "10.1109/CBMS.2013.6627850",

language = "English",

isbn = "9781479910533",

pages = "497--501",

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note = "26th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2013 ; Conference date: 20-06-2013 Through 22-06-2013",

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T1 - Reconstruction and error detection of blood vessel network from ultrasound volume data

AU - Masuda, Kohji

AU - Bossard, Antoine

AU - Sugano, Yuki

AU - Kato, Toshikazu

AU - Onogi, Shinya

PY - 2013

Y1 - 2013

N2 - Recently, we described a reconstruction method of the blood vessel network by 3D thinning to detect vessels bifurcations, which is applied to the control of microbubbles in vivo. However, that method did not include error detections and was only verified on a very simply shaped artificial blood vessel. In this paper we propose a system including an abstraction method for the blood vessel network. Such a model is then analyzed through graph theory and error patterns in the reconstructed network. We proceeded in vitro by acquiring volume data from an artificial capillary with multi-bifurcations whose diameter ranges from 0.5 to 2.0mm and with different flow velocities. We were able to reconstruct the blood vessel network of an in vitro artificial capillary with multi-bifurcations. Results show that our system successfully reconstructed the corresponding networks as much as the limitation of resolution of echography.

AB - Recently, we described a reconstruction method of the blood vessel network by 3D thinning to detect vessels bifurcations, which is applied to the control of microbubbles in vivo. However, that method did not include error detections and was only verified on a very simply shaped artificial blood vessel. In this paper we propose a system including an abstraction method for the blood vessel network. Such a model is then analyzed through graph theory and error patterns in the reconstructed network. We proceeded in vitro by acquiring volume data from an artificial capillary with multi-bifurcations whose diameter ranges from 0.5 to 2.0mm and with different flow velocities. We were able to reconstruct the blood vessel network of an in vitro artificial capillary with multi-bifurcations. Results show that our system successfully reconstructed the corresponding networks as much as the limitation of resolution of echography.

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BT - Proceedings of CBMS 2013 - 26th IEEE International Symposium on Computer-Based Medical Systems

T2 - 26th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2013

Y2 - 20 June 2013 through 22 June 2013

ER -

Reconstruction and error detection of blood vessel network from ultrasound volume data

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